This paper presents a new human-based navigation model to guide a mobile robot to intercept ground balls. The new model consists of two strategies: the optical acceleration cancellation (OAC) model, and the lateral alignment strategy. The OAC model uses a linearly decreasing cotangent function of the gaze angle to reduce the distance between the robot and the target on the ground. It determines a set of possible robot positions on the horizontal plane at every time instant. The robot laterally aligns with the target when it moves to the side. The lateral alignment strategy determines a unique robot position at each time instant. The new navigation strategy provides a simple and fast algorithm to navigate mobile robots in an open field to intercept ground balls. Visual servo controllers were designed and simulated. A high-speed mobile robot was developed to conduct interception experiments

In previous work, we demonstrated the feasibility of perceptual navigation algorithms used to intercept fly balls. In this paper we expand the optical acceleration cancellation heuristic to also intercept ground balls. We used computer simulations and experiments with mobile robots with various bail trajectories and different initial positions of the fielder to test our new model. A new robotic system with improved vision and faster processing was developed for experimentally intercepting ground balls. The results support the generality of viewer based interception heuristics for both fly balls and ground balls.

Human based algorithms; to catch fly balls have been research and studied. In the paper, the validity of the human models are tested by catching balls that are dropped vertically downward. The regular OAC (optical acceleration cancellation) and the inverted OAC models are simulated first, and then tested experimentally with a mobile robot. The simulation and the experimental results show that both methods are able to intercept the dropped ball, but the initial and final motions are different. A digital image processing program, DVRobot, was written to process digital images very quickly.

Human based vision algorithms for interception of flying balls in one-dimension have been researched and studied. We develop new perceptual strategies for three-dimensional space that are robust and simple. Results from simulations show the feasibility of human vision algorithms for ball catching. This paper discusses the experimental validation of two perceptual algorithms: linear optical trajectory and the optical acceleration cancellation.

Human navigational principles are researched and applied to mobile robotic applications. Two principles, constant optical rate and angular constancy, can be used by a fielder or mobile robot to define a trajectory for interception of a projectile without knowledge of the ball's or fielder's world coordinates. Two novel, robust, viewer-centered algorithms, a passive and an active version, are modeled and experimentally validated.